package com.whiteseason.spark.GraphX

import org.apache.spark.graphx.{Edge, Graph, VertexId}
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

object test1 {
  def main(args: Array[String]): Unit = {
    //设置运行环境
    val conf = new SparkConf().setAppName("SimpleGraphX").setMaster("local")
    conf.set("spark.testing.memory", "2147480000")
    val sc = new SparkContext(conf)
    sc.setLogLevel("WARN")

    //设置顶点数据
    val vertexArray = Array(
      (1L, ("Alice", 28)),
      (2L, ("Bob", 27)),
      (3L, ("Charlie", 65)),
      (4L, ("David", 42)),
      (5L, ("Ed", 55)),
      (6L, ("Fran", 50))
    )
    val vertex: RDD[(VertexId, (String, Int))] = sc.parallelize(vertexArray)

    //设置边
    val edgeArray = Array(
      Edge(2L, 1L, 7),
      Edge(2L, 4L, 2),
      Edge(3L, 2L, 4),
      Edge(3L, 6L, 3),
      Edge(4L, 1L, 1),
      Edge(5L, 2L, 2),
      Edge(5L, 3L, 8),
      Edge(5L, 6L, 3)
    )
    val relationships: RDD[Edge[Int]] = sc.parallelize(edgeArray)

    //创建图
    val graph = Graph(vertex, relationships)

    //找出图中年龄大于 30 的顶点
    println("---------------------找出图中年龄大于 30 的顶点------------------------")
    graph.vertices.filter { case (id, (name, occupation)) => occupation.toInt > 30 }.collect.foreach {
      case (id, (name, occupation)) => println(s"($id, ($name, $occupation))")
    }

    //找出图中属性大于 5 的边
    println("----------------------找出图中属性大于 5 的边-----------------------")
    graph.edges.filter(e => e.attr > 5).collect.foreach(e => println(s"${e.srcId} to ${e.dstId} att ${e.attr}"))

    //找出图中最大的出度、入度、度数
    println("----------------------找出图中最大的出度、入度、度数-----------------------")
    def max(a: (VertexId, Int), b: (VertexId, Int)): (VertexId, Int) = {
      if (a._2 > b._2) a else b
    }
    println("max of outDegrees:" + graph.outDegrees.reduce(max) + " max of inDegrees:" + graph.inDegrees.reduce(max) + " max of Degrees:" + graph.degrees.reduce(max))

  }

}
